Despite being seemingly a minor change, LDET demonstrates remarkable gains in open-world instance segmentation and detection. On COCO [1]}, LDET trained on VOC categories improves the average recall by 14.1 points when evaluated on non-VOC categories. Surprisingly, LDET achieves significant improvements in detecting novel objects without requiring additional annotation , LDET trained only on VOC categories (20 classes) in COCO outperforms Mask RCNN trained on all COCO categories (80 classes) when evaluating average recall on UVO [2]}. As shown in Fig. REF , LDET can generate precise object proposals as well as cover many objects in the scene.
